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Expectations Hypothesis Tests in the Presence of Model Uncertainty

Listed author(s):
  • Erdenebat Bataa

    (Centre for Growth and Business Cycles Research, Economics, University of Manchester)

  • Dong H. Kim

    ()

    (Department of Economics, Korea University and Economics, University of Manchester)

  • Denise R. Osborn

    (Centre for Growth and Business Cycles Research, Economics, University of Manchester)

We extend vector autoregressive (VAR) model based expectations hypothesis tests of the term structure by relaxing some specification assumptions in order to reflect model uncertainty. Firstly, the wild bootstrap is used to allow for conditional heteroskedasticity of unknown form in the VAR residuals. Secondly, the model selection procedure is endogenized in the bootstrap replications and supplemented with a robust multivariate autocorrelation test. Finally, a stationarity correction is introduced to prevent the bias corrected VAR coefficients from becoming explosive. When the new methodology is applied to extensive US term structure data it emerges that the model uncertainty goes a long way in explaining the empirical rejections of the theory.

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File URL: http://econ.korea.ac.kr/~ri/WorkingPapers/w0703.pdf
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Paper provided by Institute of Economic Research, Korea University in its series Discussion Paper Series with number 0703.

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Date of creation: 2007
Handle: RePEc:iek:wpaper:0703
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